Exogenous L-glutamine has preclinical antitumor activity although formal clinical translation has not been attempted. We conducted a single-arm phase 1 trial to assess the safety and preliminary efficacy of clinical-grade, US Food and Drug Administration-approved L-glutamine therapy with gemcitabine and nab-paclitaxel (GA) in participants with treatment-naive, advanced pancreatic cancer (n = 16). The primary endpoint was to determine the recommended phase 2 dose (RP2D) by adaptive Bayesian design across standard doses of GA and a dose range of 0.1-0.3 g kg-1 twice-daily oral L-glutamine. Secondary endpoints included safety and preliminary efficacy of the study combination. The primary endpoint was met with the RP2D reached at maximum doses of L-glutamine and GA. The grade ≥3 treatment-related adverse event rate was 66.7%, primarily from GA. Addition of L-glutamine to GA induced tumor shrinkage in 94% of subjects with a best overall response rate (ORR) of 44% (12.5% complete response). Median progression-free survival and overall survival (OS) were 8.5 months (95% confidence interval (CI) 6-not reached (NR)) and 22 months (95% CI 11-NR), respectively. L-Glutamine induced distinct metagenomic and metabolomic signatures on exploratory analyses in glutamine-treated subjects as a single agent, while the combination of L-glutamine and GA nearly doubled the ORR and tripled the OS compared to historical GA alone (ClinicalTrials.gov registration: NCT04634539 ).

Autism spectrum disorder, schizophrenia, and bipolar disorder are neuropsychiatric conditions that manifest early in life with a wide range of phenotypes, including repetitive behavior, agitation, and anxiety ( American Psychological Association, 2013). While the etiology of these disorders is incompletely understood, recent data implicate a role for mitochondrial dysfunction ( Norkett et al., 2017; Khaliulin et al., 2025). Mitochondria translocate to intracellular compartments to support energetics and free-radical buffering; failure to achieve this localization results in cellular dysfunction ( Picard et al., 2016). Mitochondrial Rho-GTPase 1 (Miro1) resides on the outer mitochondrial membrane and facilitates microtubule-mediated mitochondrial motility ( Fransson et al., 2003). The loss of MIRO1 is reported to contribute to the onset/progression of neurodegenerative diseases, including amyotrophic lateral sclerosis, Alzheimer's disease, and Parkinson's disease ( Kay et al., 2018). We have hypothesized that MIRO1 also has a role in nervous system development ( Lin-Hendel et al., 2016). To test this, we ablated Miro1 from cortical excitatory progenitors by crossing floxed Miro1 mice with Emx1-Cre mice and studied mice of both sex. We found that mitochondrial mislocalization in migrating excitatory neurons was associated with reduced brain weight, decreased cortical volume, and subtle cortical disorganization. Adult Miro1 conditional mutants exhibit agitative-like behaviors, including decreased nesting and abnormal home cage activity. The mice exhibited anxiety-like behavior and avoided confined spaces, features that have been linked to several human behavioral disorders. Our data link MIRO1 function with mitochondrial dynamics in the pathogenesis of several neuropsychiatric disorders and implicate intracellular mitochondrial dynamics to several anxiety-like behaviors.

Chronic low back pain (cLBP) significantly impacts quality of life, highlighting the need for safe, home-based, non-pharmacological therapies. This study (NCT04409353) evaluated three interventions utilizing Virtual Reality (VR) for managing cLBP. 385 participants were randomized across three groups: Skills-Based VR (biofeedback, interoceptive training, and relaxation), Distraction VR (immersive 360-degree videos), and Sham VR (2D videos). The primary outcome was the change in PROMIS Pain Interference (PI). Secondary outcomes included the change in physical function, anxiety, depression, sleep disturbance, opioid use, and Fitbit-measured steps and sleep efficiency. No significant differences were observed between active VR (Skills-Based and Distraction) and Sham VR for the primary or most secondary outcomes. Secondary findings indicated a greater reduction in daily opioid use in the Distraction VR group compared to Sham VR (p = 0.009), and exploratory analyses revealed that baseline anxiety significantly predicted PROMIS-PI improvement within the Skills-Based VR (p = 0.025) group. Depression symptoms showed no such association. Adverse events were predominantly mild and self-limited, with cybersickness being the most common. Neither active VR program outperformed Sham VR for the primary outcome. High adherence across groups underscored the feasibility of home-based VR. Future studies, powered to test anxiety-moderated treatment effects and opioid-use reduction as primary outcomes, are warranted.

1033 Background: MBC remains incurable despite recent incorporation of ADCs. The optimal sequencing of FDA-approved ADCs such as trastuzumab deruxtecan (T-DXd) or sacituzumab govitecan (SG) are lacking and real-world data have shown cross resistance between the ADCs. The current study aims to develop a clinical diagnostic assay to guide optimal treatment for patients with MBC using digital patient organoid (DPO) in patients with MBC receiving or progressed on ADCs for a precision tool to guide therapy in post-ADC resistance setting. Methods: An institutional IRB was established for prospective collection of fresh tumor biopsies in patients with MBC undergoing ADC therapy. DPO drug sensitivity tests were conducted and analyzed for association with clinical outcome using progression free survival (PFS). DPO tests include ADCs (T-DXd, SG, Dato-DXd) or single agent chemo dosing experiments to determine drug sensitivities (AUC values calculated from CTG readouts) for downstream correlation analyses. Results: Between 09/2024–01/2026, 41 fresh tumor tissues were collected and processed. 22 samples had sufficient viable cells to pass QC for DPO establishment and were successfully assayed and 12 failed QC, giving a DPO establishment success rate of 64.71%. DPO success rates varies by breast cancer subtypes: 100% in HER2+, 73% in TNBC and 56% in HR+HER2- BC. and sites of metastasis. Sites of metastasis (met) also impacted DPO success rates: lymph node 0%, liver met 33%, skin met 60%, breast/ascites 100%. Organoids typically established and expanded within 7-14 days post-biopsy. The DPO drug assays were conducted for ADCs, payloads, and chemotherapy agents testing. Analysis revealed that prior clinical exposure and progression on an ADC correlated with reduced DPO sensitivity to the same agent, consistent with acquired resistance. The platform was capable of delineating between target- versus payload-based resistance. Notably, DPOs from heavily pretreated patients were often resistant to both ADCs but remained responsive to alternative agents, highlighting potential therapeutic opportunities. Conclusions: The DPO platform shows promise in predicting treatment responses and differentiating resistance mechanisms to ADCs in MBC. This approach provides a foundation for rational treatment selection in patients with MBC with prior ADC resistance.

In this article, we propose a phase I-II design in two stages for the combination of molecularly targeted therapies. The design is motivated by a published case study that combines a MEK and a PIK3CA inhibitors; a setting in which higher dose levels do not necessarily translate into higher efficacy responses. The goal is therefore to identify dose combination(s) with a prespecified desirable risk-benefit trade-off. We propose a flexible cubic spline to model the marginal distribution of the efficacy response. In stage I, patients are allocated following the escalation with overdose control (EWOC) principle whereas, in stage II, we adaptively randomize patients to the available experimental dose combinations based on the continuously updated model parameters. A simulation study is presented to assess the design's performance under different scenarios, as well as to evaluate its sensitivity to the sample size and to model misspecification. Compared to a recently published dose finding algorithm for biologic drugs, our design is safer and more efficient at identifying optimal dose combinations.

Supplementary Methods S1 provides a comprehensive statistical description of the two applied predictive survival models (PC Cox model and PC Cox BLUP model).

Supplementary Figure S7 presents a screenshot of the web tool; the supplementary data provides instructions for utilizing the web-based treatment discontinuation predictive tool developed based on the predictive survival models.

Supplementary Figure S6 (a) shows the actual eight PROs of patient 1 at two time points, baseline, and 6 months (shown by the black dotted line). This patient is also overweight at baseline (25 < BMI < 30). In the clinical data set, this patient discontinued treatment at 14 months, but this information was not used in the model. Supplementary Figure S6 (b) shows the estimated probability of treatment discontinuation for patient 1 anytime after 6 months but before 18 months. Supplementary Figure S6 (c) shows similar information for patient 2 who is also overweight. However, patient 2 completed treatment by 60 months. Supplementary Figure S6 (d) shows the estimated probability of treatment discontinuation for patient 2 anytime after 6 months but before 18 months.

Supplementary Table S3 provides information about the number of patients with missing adverse events at each timepoint for tamoxifen treatment.

Supplementary Figure S5 illustrates the estimated time-dependent ROC curves using the PCCox and PCCox BLUP models in the validation cohort for tamoxifen treatment. The area under the ROC curve (AUC) and its corresponding 95% confidence interval for the four sets of s and tau are embedded within the plots.

BACKGROUND:The PRO-CTCAE Measurement System was designed to enhance the quality of the standard toxicity evaluation in clinical trials. We developed a substudy within NRG-BR004, a phase III clinical trial in patients with newly documented HER2-positive metastatic breast cancer (MBC), to examine the added value and feasibility of frequent PRO-CTCAE data collection. METHODS:Patients were asked to complete 23 PRO-CTCAE items assessing 12 symptoms. Electronic PRO (ePRO) reporting was preferred; however, paper administration was allowed. The data on items assessed before treatment initiation, then weekly during Cycles 1-2 (12 weeks), are presented herein. Feasibility of frequent assessment with ePRO reporting was assessed using these data and was predefined as ≥25% of patients being compliant (submitted ≥75% of scheduled assessments). We also examined PRO-CTCAE and clinician-reported CTCAE data for key symptoms using maximum toxicity grade and the toxicity index (TI). RESULTS:Overall, 80% of patients (82 of 103) were compliant with expected weekly assessments (90% CI = 0.72 to 0.86). For all symptoms, the median maximum grade (TI value) of clinician-reported CTCAE was lower than the median maximum score (TI value) of patient-reported PRO-CTCAE. The differences in the data trend for weekly vs less frequent assessment were more apparent when data were evaluated using the TI vs the maximum score. CONCLUSIONS:Weekly assessments within the first two chemotherapy cycles were feasible in this trial of MBC patients. As expected, patients reported greater severity of symptoms than clinicians. Demonstrating the feasibility of frequent assessment could have implications for future research and clinical practice. CLINICALTRIALS.GOV:NCT03199885 (https://clinicaltrials.gov/study/NCT03199885).

Supplementary Table S1 outlines all predictors employed to predict treatment discontinuation, including the predictor variable name, variable description, variable type, and whether the data was collected over time or only at baseline.

Blood glucose (BG) in hospitalized patients is influenced by numerous clinical factors, including medications not traditionally associated with glycemic control. To better characterize these effects, we analyzed electronic health record data from 97,281 inpatient encounters (2014-2022), capturing 3,009,686 point-of-care BG measurements. We extracted over 300 variables-medications, labs, and socio-demographics-and used Lasso, ridge, and elastic net regression for predictive modeling, alongside propensity score matching (PSM) for causal inference. While Lasso reduced multicollinearity, it often assigned implausible coefficient directions. In contrast, PSM yielded clinically consistent and interpretable estimates, identifying 55 variables significantly associated with BG changes, without shrinking coefficients to zero of known BG-modulating drugs. Findings were validated in a 2022-2024 test set of 27,847 encounters. This work highlights the value of causal inference in observational EHR analysis and identifies both established and under-recognized (e.g., cholecalciferol) medication effects on BG, offering insights that inform safer inpatient glycemic management.

BACKGROUND:Advancements in cancer therapies and improvements in survival have led to an increasing need to understand the impact of treatment on both severe and low-grade persisting symptoms and treatment-related toxicities. The National Cancer Institute launched the Cancer Moonshot Tolerability Consortium in 2018 to develop methods to analyze clinical and patient-reported tolerability data. METHODS:Through this initiative, the toxicity index (TI) was applied in the analysis of clinical trial tolerability data, and its performance was compared to other existing scoring methods. The TI is a tool developed to quantify the cumulative burden of all levels of clinician-graded toxicity data using Common Terminology Criteria for Adverse Events and patient-reported toxicity. This review describes the statistical properties of the TI and highlights key findings on the utility of the TI in summarizing tolerability data and its applications to existing clinical trial data. RESULTS:Compared to other commonly used summary measures, the TI was shown to be more efficient and increased the statistical power to detect treatment differences. The TI was also applied to existing toxicity and patient-reported symptom data from selected trials, where it was used to predict dose-limiting toxicities and treatment discontinuation. Visualization methods were explored and incorporated into interactive web-based research and patient-facing tools to enhance the interpretability and clinical utility of the TI. CONCLUSION:In conclusion, the TI is a useful summary measure that can be applied to a range of adverse event and patient-reported data to maximize the information collected and provide a more accurate and complete account of the tolerability experience. Future research will focus on extending applications of the TI and exploring its use for the design of clinical trials.

Supplementary Methods S2 provides a statistical description of the prediction error used to assess the model performance.

Supplementary Table S4 presents the optimal risk thresholds (c) and estimates of diagnostic measures such as sensitivity, specificity, and accuracy, along with their corresponding 95% confidence intervals. These values are derived from the PCCox and PCCox BLUP models based on treatment, as applied in the validation cohort.

Despite great interest, there is limited clinical evidence to support the use of a ketogenic diet (KD) for cancer patients. We conducted a single-arm phase 1 trial of a KD among patients with recently diagnosed glioblastoma (GBM) receiving standard-of-care (SOC) treatment. Adults with GBM within 3 months of diagnosis followed a supervised 16-week intervention of a 3:1 KD (Fat(g): Carbohydrate + Protein(g)) plus SOC chemoradiation. The primary outcome was safety, evaluated by weekly assessments of weight and body mass index (BMI). Secondary outcomes included feasibility (pre-specified as > 50% of patients maintaining blood ketone levels > 0.3 mM over 50% of study days), progression-free survival (PFS), overall survival (OS), health-related quality-of-life, and cognitive function. Twice daily blood glucose and ketones, weight/BMI, physical activity, and sleep were assessed by remote monitoring. Seventeen patients were evaluable: 53% women, median age 55, median Karnofsky Performance Status 85. All subjects met the primary safety objective with no instances of excessive weight loss or related serious adverse events. Adherence was high: all 17 patients maintained nutritional ketosis (≥ 0.3 mM/dL) > 50% of study days. Median PFS and OS were 12.9 months and 29.4 months from KD initiation respectively. Quality of Life, symptom control, and cognitive function remained stable or improved, although these did not reach statistical significance. This phase 1 trial demonstrates that KD is safe and feasible for GBM patients receiving SOC, may improve outcomes, and provides a foundation for an NCI-funded multicenter randomized diet trial to assess efficacy that is currently underway.

Supplementary Figure S3 shows the estimated discontinuation curves by training dataset and validation cohort for the tamoxifen-treated patients.